Senior Director of Engineering, Developer and Agent Experience

Toast Toast · Enterprise · Boston, MA +1 · R & D : Cloud Service Infra

Lead the development of Toast's AI-native engineering operating system, transforming software development from idea to production. This hands-on leadership role focuses on systemizing AI across the SDLC and PDLC, defining and delivering platforms, workflows, and guardrails for AI-embedded development. Responsibilities include building the core platform for AI-native development, designing AI-driven systems for code generation, re-architecting the developer experience, and leading a specialized AI platform engineering organization.

What you'd actually do

  1. Define and deliver the core platform enabling AI-native development, including the model access layer (LLMs, routing, governance), agent orchestration systems (code, test, review, deploy), prompt/specification frameworks, coding harnesses and an internal AI marketplace
  2. Design and implement AI-driven development systems that convert PRDs and design specs into executable workflows, enabling the automated generation of code, tests, documentation, and infrastructure
  3. Re-architect the developer experience across the inner loop (local development, testing, iteration) and outer loop (CI/CD, deployment, release) to reduce friction in PR creation, code reviews, and validation
  4. Partner with Engineering, Product and Design leaders to transition individual AI tool usage into standardized workflows, establishing tooling defaults, playbooks, and training to ensure active AI usage across R&D
  5. Build and lead a focused organization specialized in AI platform engineering, agent systems, automation and developer experience integration

Skills

Required

  • applied AI and agentic architectures
  • developer platforms
  • internal engineering systems
  • CI/CD
  • build systems
  • platform tooling
  • end-to-end workflows
  • prompt engineering
  • developer-facing API/platform design
  • usage-based cost models/platform governance
  • organization-wide adoption of new tools, workflows, playbooks, and structural standards
  • PCI, SOX, or equivalent compliance experience

Nice to have

  • AI marketplace
  • model-agnostic harness layer
  • open-weight and self-hosted options
  • portable skills, plugins, and agents

What the JD emphasized

  • definitive internal authority
  • deep technical proficiency in applied AI and agentic architectures
  • operating inside real compliance constraints — PCI, SOX, or equivalent

Other signals

  • AI-native engineering operating system
  • systemizing AI across the software development lifecycle
  • AI embedded at every step
  • agent orchestration systems
  • AI-driven development systems